d458ed1b34
All sibling services on the box manage schema with Alembic (async env, `alembic upgrade head` in the compose command). matchmaking-v2 was the outlier (Base.metadata.create_all + no migration for the new user_feed.exhausted_at column). Bring it onto the pattern: - alembic.ini + alembic/env.py (async, URL from settings.DATABASE_URL, target = Base.metadata) + script.py.mako — copied/adapted from user-service. - versions/0001_baseline: the current prod schema (user_feed WITHOUT exhausted_at + opportunity_state). - versions/0002_pool_and_exhausted: CREATE user_job_pool + ADD user_feed.exhausted_at (additive). - Dockerfile: COPY alembic.ini + alembic/. requirements: alembic>=1.13.0. Verified both paths: fresh DB → upgrade head builds all 3 tables; prod-like (existing tables+data) → stamp 0001 → upgrade runs ONLY 0002, existing rows survive. 64 tests pass. PROD ADOPTION (one-time): `alembic stamp 0001_baseline` on RDS before the first deploy, then the compose's `alembic upgrade head` applies 0002.
matchmaking-v2 (Scout)
Fresh, on-demand matchmaking service replacing the dead nightly aggregator. Same agent-mesh mold as the other GrowQR services (FastAPI · a2a card · /a2a/tasks · orchestrator-routed). Not a drop-in — it keeps the existing 4 skills working and adds new actions from scratch.
Layout
app/
main.py FastAPI app (card + /a2a/tasks + /api/v1/health), lifespan worker
config.py lean settings (no corpus DB, no scrape schedule)
a2a/ card.py (discovery), auth.py (bearer), tasks.py (orchestrator entry)
agent/session.py Session: on_session_start / on_user_action dispatch ← the brain
adk/worker.py Redis-Streams worker (graceful no-op without Redis)
api/v1/health.py /api/v1/health
engine/
board_adapters/ ScoutPrefs → Apify actor inputs (Naukri-first, verified maps)
... the §3 cascade (normalize→filter→utility→fusion→rerank) lands here
contracts/ Pydantic contracts (user_context, transport, …) — added per slice
research/ docs/ (ENGINE_DESIGN, SIGNAL_AUDIT_V2, ENGINE_INPUTS, …) + poc/ (auto-apply)
Contract (how it connects)
Frontend useAgentSession (page "job-matching") → orchestrator (routes by card name
= matchmaking-service) → POST /a2a/tasks {action, params, user_context} → Session pushes
agent_data{action,data} → orchestrator → frontend latestData[action].
Skills: existing get_feed · sync_preferences · record_feedback · get_opportunity_detail;
new run_search · tailor_resume · submit_application · get_apply_proof (stubbed). Each new action
needs: card skill (here) + orchestrator action-map entry + frontend sendAction wiring.
Run (local)
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8006
# card: GET http://localhost:8006/.well-known/agent-card.json
# health: GET http://localhost:8006/api/v1/health
# action: POST http://localhost:8006/a2a/tasks (Bearer dev-a2a-key)
Build order (full-stack slices)
- ✅ scaffold (this) — bootable skeleton, contract wired, handlers stubbed.
- on-demand
run_search— board_adapters → Apify → engine cascade → ranked feed (+ frontend wire). - feedback labels +
record_feedback. 3.tailor_resume. 4.submit_application+get_apply_proof. - cut over from old
:8006, decommission corpus.